Nisansa Dilushan de Silva

I am a lecturer at the Department of Computer Science & Engineering, University of Moratuwa, Sri Lanka. I obtained my Ph.D (2020, advisor: Dejing Dou) and MS (2016) degrees in Computer and Information Science from University of Oregon, USA and my BSc (Hons) in Computer Science & Engineering (2011) degree from University of Moratuwa. I joined University of Moratuwa as a lecturer in 2011. From 2013 to 2014, I worked as a researcher at LIRNEasia. In 2018, I worked as a Givens Associate at Argonne National Laboratory, USA. I have over 40 peer reviewed publications in the field of computer science, mostly under the subfields of Natural Language Processing and Artificial Intelligence, earning more than 400 citations. I am also an associate member of the IESL.

Professional Experience

  • Present 2020

    Senior Lecturer

    Department of Computer science & Engineering, University of Moratuwa,
    Sri Lanka

  • 2021 2020

    Research Fellow

    LIRNEasia,
    Sri Lanka

  • 2020 2014

    Graduate Research/Teaching Fellow

    University of Oregon, Department of Computer and Information Science,
    USA.

  • 2018 2018

    Givens Associate

    Argonne National Laboratory,
    USA.

  • 2020 2011

    Lecturer

    Department of Computer science & Engineering, University of Moratuwa,
    Sri Lanka

  • 2014 2013

    Researcher

    LIRNEasia,
    Sri Lanka

  • 2014 2013

    Visiting Lecturer

    Northshore College of Business and Technology,
    Sri Lanka

Education

  • Ph.D. 2020

    Ph.D. in Computer & Information Science

    University of Oregon, USA

  • MS 2016

    MS in Computer & Information Science

    University of Oregon, USA

  • BSc2011

    B.Sc Engineering (Hons)in Computer Science & Engineering

    University of Moratuwa, Sri Lanka

Featured Research

Identifying Legal party Members from Legal Opinion Text using Natural Language Processing


M. de Almeida, C. Samarawickrama, N. de Silva, G. Ratnayaka, and S. Perera

The 23rd International Conference on Information Integration and Web Intelligence, 2021, pp. 259--266,

Law and order is a field that can highly benefit from the contribution of Natural Language Processing (NLP) to its betterment. An area in which NLP can be of immense help is, information retrieval from legal documents which function as legal databases. The extraction of legal parties from the aforementioned legal documents can be identified as a task of high importance since it has a significant impact on the proceedings of contemporary legal cases. This study proposes a novel deep learning methodology which can be effectively used to find a solution to the problem of identifying legal party members in legal documents. In addition to that, in this paper, we introduce a novel data set which is annotated with legal party information by an expert in the legal domain. The deep learning model proposed in this study provides a benchmark for the legal party identification task on this data set. Evaluations for the solution presented in the paper show that our system has 90.89\% precision and 91.69\% recall for an unseen paragraph from a legal document, thus conforming the success of our attempt.